Xing-Yue Ge, Juergen Funk, Tom Albrecht, Merima Birkhimer, Moritz Gilsdorf, Matthew Hayes, Fangyao Hu, Pierre Maliver, Mark McCreary, Trung Nguyen, Fernando Romero-Palomo, Shanon Seger, Reina N Fuji, Vanessa Schumacher, Ruth Sullivan
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Toxicologic Pathology Forum: A Roadmap for Building State-of-the-Art Digital Image Data Resources for Toxicologic Pathology in the Pharmaceutical Industry.
Digitization of histologic slides brings with it the promise of enhanced toxicologic pathology practice through the increased application of computational methods. However, the development of these advanced methods requires access to substrate image data, that is, whole slide images (WSIs). Deep learning methods, in particular, rely on extensive training data to develop robust algorithms. As a result, pharmaceutical companies interested in leveraging computational methods in their digital pathology workflows must first invest in data infrastructure to enable data access for both data scientists and pathologists. The process of building robust image data resources is challenging and includes considerations of generation, curation, and storage of WSI files, and WSI access including via linked metadata. This opinion piece describes the collective experience of building resources for WSI data in the Roche group. We elaborate on the challenges encountered and solutions developed with the goal of providing examples of how to build a data resource for digital pathology analytics in the pharmaceutical industry.
期刊介绍:
Toxicologic Pathology is dedicated to the promotion of human, animal, and environmental health through the dissemination of knowledge, techniques, and guidelines to enhance the understanding and practice of toxicologic pathology. Toxicologic Pathology, the official journal of the Society of Toxicologic Pathology, will publish Original Research Articles, Symposium Articles, Review Articles, Meeting Reports, New Techniques, and Position Papers that are relevant to toxicologic pathology.